Localization of Sensorimotor Cortex Using Navigated Transcranial Magnetic Stimulation and Magnetoencephalography.

The mapping of the sensorimotor cortex gives information about the cortical motor and sensory functions. Typical mapping methods are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG). The differences between these mapping methods are, however, not fully known. TMS center of gravities (CoGs), MEG somatosensory evoked fields (SEFs), corticomuscular coherence (CMC), and corticokinematic coherence (CKC) were mapped in ten healthy adults. TMS mapping was performed for first dorsal interosseous (FDI) and extensor carpi radialis (ECR) muscles. SEFs were induced by tactile stimulation of the index finger. CMC and CKC were determined as the coherence between MEG signals and the electromyography or accelerometer signals, respectively, during voluntary muscle activity. CMC was mapped during the activation of FDI and ECR muscles separately, whereas CKC was measured during the waving of the index finger at a rate of 3-4 Hz. The maximum CMC was found at beta frequency range, whereas maximum CKC was found at the movement frequency. The mean Euclidean distances between different localizations were within 20 mm. The smallest distance was found between TMS FDI and TMS ECR CoGs and longest between CMC FDI and CMC ECR sites. TMS-inferred localizations (CoGs) were less variable across participants than MEG-inferred localizations (CMC, CKC). On average, SEF locations were 8 mm lateral to the TMS CoGs (p < 0.01). No differences between hemispheres were found. Based on the results, TMS appears to be more viable than MEG in locating motor cortical areas.

Correction to: Extent and Location of the Excitatory and Inhibitory Cortical Hand Representation Maps: A Navigated Transcranial Magnetic Stimulation Study.

The original version of this article unfortunately contained an error. An error in the transformation between coordinate systems used to derive part of the results has been noticed.

Efficient Mapping of the Motor Cortex with Navigated Biphasic Paired-Pulse Transcranial Magnetic Stimulation.

Navigated transcranial magnetic stimulation (nTMS) can be applied to locate cortical muscle representations. Usually, single TMS pulses are targeted to the motor cortex with the help of neuronavigation and by measuring motor evoked potential (MEP) amplitudes from the peripheral muscles. The efficacy of single-pulse TMS to induce MEPs has been shown to increase by applying facilitatory paired-pulse TMS (ppTMS). Therefore, the aim was to study whether the facilitatory ppTMS could enable more efficient motor mapping. Biphasic single-pulse TMS and ppTMS with inter-stimulus intervals (ISIs) of 1.4 and 2.8 ms were applied to measure resting motor thresholds (rMTs) as a percentage of the maximal stimulator output and to determine the cortical representation areas of the right first dorsal interosseous muscle in healthy volunteers. The areas, shapes, hotspots, and center of gravities (CoGs) of the representations were calculated. Biphasic ppTMS with ISI of 1.4 ms resulted in lower rMTs than those obtained with the other protocols (p = 0.001). With ISI of 2.8 ms, rMT was lower than with single-pulse TMS (p = 0.032). The ppTMS mapping was thus performed with lower intensity than when using single-pulse TMS. The areas, shapes, hotspots, and CoGs of the muscle representations were in agreement. Hence, biphasic ppTMS has potential in the mapping of cortical hand representations in healthy individuals as an alternative for single-pulses, but with lower stimulation intensity by utilizing cortical facilitatory mechanism. This could improve application of nTMS in subjects with low motor tract excitability.

Minimum-Norm Estimation of Motor Representations in Navigated TMS Mappings.

Navigated transcranial magnetic stimulation (nTMS) can be applied to locate and outline cortical motor representations. This may be important, e.g., when planning neurosurgery or focused nTMS therapy, or when assessing plastic changes during neurorehabilitation. Conventionally, a cortical location is considered to belong to the motor cortex if the maximum electric field (E-field) targeted there evokes a motor-evoked potential in a muscle. However, the cortex is affected by a broad E-field distribution, which tends to broaden estimates of representation areas by stimulating also the neighboring areas in addition to the maximum E-field location. Our aim was to improve the estimation of nTMS-based motor maps by taking into account the E-field distribution of the stimulation pulse. The effect of the E-field distribution was considered by calculating the minimum-norm estimate (MNE) of the motor representation area. We tested the method on simulated data and then applied it to recordings from six healthy volunteers and one stroke patient. We compared the motor representation areas obtained with the MNE method and a previously introduced interpolation method. The MNE hotspots and centers of gravity were close to those obtained with the interpolation method. The areas of the maps, however, depend on the thresholds used for outlining the areas. The MNE method may improve the definition of cortical motor areas, but its accuracy should be validated by comparing the results with maps obtained with direct cortical stimulation of the cortex where the E-field distribution can be better focused.

Extent and Location of the Excitatory and Inhibitory Cortical Hand Representation Maps: A Navigated Transcranial Magnetic Stimulation Study.

Voluntary muscle action and control are modulated by the primary motor cortex, which is characterized by a well-defined somatotopy. Muscle action and control depend on a sensitive balance between excitatory and inhibitory mechanisms in the cortex and in the corticospinal tract. The cortical locations evoking excitatory and inhibitory responses in brain stimulation can be mapped, for example, as a pre-surgical procedure. The purpose of this study was to find the differences between excitatory and inhibitory motor representations mapped using navigated transcranial magnetic stimulation (nTMS). The representations of small hand muscles were mapped to determine the areas and the center of gravities (CoGs) in both hemispheres of healthy right-handed volunteers. The excitatory representations were obtained via resting motor evoked potential (MEP) mapping, with and without a stimulation grid. The inhibitory representations were mapped using the grid and measuring corticospinal silent periods (SPs) during voluntary muscle contraction. The excitatory representations were larger on the dominant hemisphere compared with the non-dominant (p < 0.05). The excitatory CoGs were more medial (p < 0.001) and anterior (p < 0.001) than the inhibitory CoGs. The use of the grid did not influence the areas or the CoGs. The results support the common hypothesis that the MEP and SP representations are located at adjacent sites. Furthermore, the dominant hemisphere seems to be better organized for controlling excitatory motor functions with respect to TMS. In addition, the inhibitory representations could provide further information about motor reorganization and aid in surgery planning when the functional cortical representations are located in abnormal cortical regions.

Respiratory event index underestimates severity of sleep apnea compared to apnea-hypopnea index.

Polygraphy (PG) is often used to diagnose obstructive sleep apnea (OSA). However, it does not use electroencephalography, and therefore cannot estimate sleep time or score arousals and related hypopneas. Consequently, the PG-derived respiratory event index (REI) differs from the polysomnography (PSG)-derived apnea-hypopnea index (AHI). In this study, we comprehensively analyzed the differences between AHI and REI. Conventional AHI and REI were calculated based on total sleep time (TST) and total analyzed time (TAT), respectively, from two different PSG datasets (n = 1561). Moreover, TAT-based AHI (AHITAT) and TST-based REI (REITST) were calculated. These indices were compared keeping AHI as the gold standard. The REI, AHITAT, and REITST were significantly lower than AHI (p < 0.0001, p ≤ 0.002, and p ≤ 0.01, respectively). The total classification accuracy of OSA severity based on REI was 42.1% and 72.8% for two datasets. Based on AHITAT, the accuracies were 68.4% and 85.9%, and based on REITST, they were 65.9% and 88.5% compared to AHI. AHI was most correlated with REITST (r = 0.98 and r = 0.99 for the datasets) and least with REI (r = 0.92 and r = 0.97). Compared to AHI, REI had the largest mean absolute errors (13.9 and 6.7) and REITST the lowest (5.9 and 1.9). REI had the lowest sensitivities (42.1% and 72.8%) and specificities (80.7% and 90.9%) in both datasets. Based on these present results, REI underestimates AHI. Furthermore, these results indicate that arousal-related hypopneas are an important measure for accurately classifying OSA severity.

Arousal burden is highest in supine sleeping position and during light sleep.

STUDY OBJECTIVES: Arousal burden (AB) is defined as the cumulative duration of arousals during sleep divided by the total sleep time. However, in-depth analysis of AB related to sleep characteristics is lacking. Based on previous studies addressing the arousal index (ArI), we hypothesized that the AB would peak in the supine sleeping position and during non-rapid eye movement stage 1 (N1) and show high variability between scorers. METHODS: Nine expert scorers analyzed polysomnography recordings of 50 participants, the majority with an increased risk for obstructive sleep apnea. AB was calculated in different sleeping positions and sleep stages. A generalized estimating equation was utilized to test the association between AB and sleeping positions, sleep stages, and scorers. The correlation between AB and ArI was tested with Spearman's rank-order correlation. RESULTS: AB significantly differed between sleeping positions (p<0.001). The median AB in the supine sleeping position was 47-62% higher than in the left and right position. The AB significantly differed between the sleep stages (p<0.001); the median AB was more than 200% higher during N1 than during other sleep stages. In addition, the AB differed significantly between scorers (p<0.001) and correlated strongly with ArI (r=0.935, p<0.001). CONCLUSIONS: AB depends on the sleeping position, sleep stage, and scorer as hypothesized. AB behaved similarly as the ArI, but the high variability in the ABs between scorers indicates a potential limitation caused by subjective manual scoring. Thus, the development of more accurate techniques for scoring arousals is required before AB can be reliably utilized.

Fast acquisition of resting motor threshold with a stimulus-response curve - Possibility or hazard for transcranial magnetic stimulation applications?

OBJECTIVE: Previous research has suggested that transcranial magnetic stimulation (TMS) related cortical excitability measures could be estimated quickly using stimulus-response curves with short interstimulus intervals (ISIs). Here we evaluated the resting motor threshold (rMT) estimated with these curves. METHODS: Stimulus-response curves were measured with three ISIs: 1.2-2 s, 2-3 s, and 3-4 s. Each curve was formed with 108 stimuli using stimulation intensities ranging from 0.75 to 1.25 times the rMTguess, which was estimated based on motor evoked potential (MEP) amplitudes of three scout responses. RESULTS: The ISI did not affect the rMT estimated from the curves (F = 0.235, p = 0.683) or single-trial MEP amplitudes at the group level (F = 0.90, p = 0.405), but a significant subject by ISI interaction (F = 3.64; p < 0.001) was detected in MEP amplitudes. No trend was observed which ISI was most excitable, as it varied between subjects. CONCLUSIONS: At the group level, the stimulus-response curves are unaffected by the short ISI. At the individual level, these curves are highly affected by the ISI. SIGNIFICANCE: Estimating rMT using stimulus-response curves with short ISIs impacts the rMT estimate and should be avoided in clinical and research TMS applications.

Minimum-Norm Estimation of TMS-Activated Motor Cortical Sites in Realistic Head and Brain Geometry.

Navigated transcranial magnetic stimulation (nTMS) is a widely used tool for motor cortex mapping. However, the full details of the activated cortical area during the mapping remain unknown due to the spread of the stimulating electric field (E-field). Computational tools, which combine the E-field with physiological responses, have potential for revealing the activated source area. We applied the minimum-norm estimate (MNE) method in a realistic head geometry to estimate the activated cortical area in nTMS motor mappings of the leg and hand muscles. We calculated the MNE also in a spherical head geometry to assess the effect of the head model on the MNE maps. Finally, we determined optimized coil placements based on the MNE map maxima and compared these placements with the initial hotspot placement. The MNE maps generally agreed well with the original motor maps: in the realistic head geometry, the distance from the MNE map maximum to the motor map center of gravity (CoG) was 8.8 ± 4.6 mm in the leg motor area and 6.6 ± 2.5 mm in the hand motor area. The head model did not have a significant effect on these distances; however, it had a significant effect on the distance between the MNE CoG and the motor map ( ). The optimized coil locations were < 1 cm from the initial hotspot in 7/10 subjects. Further research is required to determine the level of anatomical detail and the optimal mapping parameters required for robust and accurate localization.